Independent Factor Analysis

@article{Attias1999IndependentFA,
  title={Independent Factor Analysis},
  author={Hagai Attias},
  journal={Neural Computation},
  year={1999},
  volume={11},
  pages={803-851}
}
We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the number of mixtures differs from the number of sources and the data are noisy. IFA is a two-step procedure. In the first step, the source densities… CONTINUE READING
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